Research
Publications
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Does the implementation of external oversight in policing improve public perceptions of police legitimacy? Civilian review boards (CRBs) are frequently promoted as mechanisms to enhance the legitimacy of police agencies by providing independent oversight. Despite public support for CRBs, their adoption and effectiveness remain limited, raising concerns about their actual impact on procedural fairness and police legitimacy. This study assesses the role of CRBs in shaping public perceptions by examining various decision-making scenarios involving police chiefs and CRBs. Using a survey experiment fielded to 2,503 respondents, we investigate whether CRBs enhance legitimacy when they either coincide with or conflict with police chiefs’ determinations in cases of officer misconduct. Our findings suggest that while CRBs may enhance perceptions of procedural fairness for some, particularly those with negative views of police, their involvement does not generally increase legitimacy. In fact, when CRBs conflict with police chiefs, they may diminish public trust in both policing and civilian oversight and further entrench politically polarized attitudes towards policing. These results provide empirical evidence to support concerns that CRBs might not fulfill their intended role in enhancing police legitimacy, especially in cases of institutional disagreement
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Every year, Americans elect hundreds of thousands of candidates to local public office, typically in low-attention, nonpartisan races. How do voters evaluate candidates in these sorts of elections? Previous research suggests that, absent party cues, voters rely on a set of heuristic shortcuts—including the candidate’s name, profession, and interest group endorsements—to decide whom to support. In this paper, we suggest that community embeddedness—a candidate’s roots and ties to the community—is particularly salient in these local contests. We present evidence from a conjoint survey experiment on a nationally representative sample of American voters. We estimate the marginal effect on vote share of candidate attributes such as gender, race, age, profession, interest group endorsements, and signals of community embeddedness— specifically homeownership and residency duration. We find that voters, regardless of political party, have strong preferences for community embeddedness. Strikingly, the magnitude of the residency duration effect rivals that of prior political experience.
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This paper examines the extent to which social pressures can foster greater responsiveness among public officials. I conduct a non-deceptive field experiment on 1400 city executives across all 50 states and measure their level of responsiveness to open records requests. I use two messages to prime social pressure. The first treatment centers on the norm and duty to be responsive to the public’s request for transparency. The second treatment is grounded in the peer effect literature, which suggests that individuals change their behavior in the face of potential social sanctioning and accountability. I find no evidence that mayors are affected by priming the officials’ duty to the public. The mayors who received the peer effects prime were 6–8 percentage points less likely to respond, which suggests a “backfire effect.” This paper contributes to the growing responsiveness literature on the local level and the potential detrimental impact of priming peer effects.
Link to paper here.
NotebookLLM Podcast -
Urban–rural differences in partisan political loyalty are as familiar in the United States as they are in other countries. In this paper, we examine Gallup survey data from the early-2000s through 2018 to understand the urban–rural fissure that has been so noticeable in recent elections. We consider the potential mechanisms of an urban–rural political divide. We suggest that urban and rural dwellers oppose each other because they reside in far apart locations without much interaction and support different political parties because population size structures opinion quite differently in small towns compared with large cities. In particular, we consider the extent to which the compositional characteristics (i.e., race, income, education, etc.) of the individuals living in these locales drives the divide. We find that sizable urban–rural differences persist even after accounting for an array of individual-level characteristics that typically distinguish them.
Link to the paper here.
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Link to Oxford Bibliographies here.
Other Publications
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Link here.
Working Papers
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Given a patchwork system of overlapping local institutions, can residents direct public policy? Current approaches to representation at the local level may present a distorted view of how democracy operates because they fail to account for the overlapping nature of institutions. To address this gap, I first implement a framework that incorporates multiple overlapping governing institutions: cities, counties, school districts, and special districts. Second, I use data from more than 500,000 survey responses to estimate a novel measure of local ideological preferences for cities over time. Finally, to assess the impact of ideology on public policy outcomes, I use a Bayesian within-between random effects model. This methodology yields three major findings. First, I demonstrate that cross-sectional responsiveness exists. Second, I find evidence for dynamic responsiveness in spending but inconclusive evidence for taxation. Third, I provide descriptive evidence that consolidated governance fosters greater responsiveness. I reframe the responsiveness discussion from a single governing unit to a holistic system of overlapping institutions and provide the strongest evidence to date that local governments respond dynamically to the ideology of citizens.
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Where and why are discriminatory ordinances adopted? Theories of racial threat suppose that members of a racial majority group regard the presence of minorities as a threat to their socio-political status and implement policies to hurt that minority population. I use the racial threat hypothesis to examine the adoption of criminal activity nuisance ordinances (or crime-free housing laws). These ordinances allow officials to designate specific properties and residents as nuisances after repeated police interactions. After that designation, property owners are penalized with fines or the seizure of property if they do not respond by removing the residents. Using data from Ohio municipalities, I find that the racial composition of cities predicts the emergence of criminal activity nuisance ordinances. I attempt to rule out alternative hypotheses surrounding the proportion of renter-occupied housing, crime, and poverty. In further exploring the results, I use a machine learning technique called Random Forests to uncover the discontinuity or “tipping point” where the propensity for adopting such a policy sharply increases or decreases. This research speaks to the generalizability of the racial threat hypothesis, the importance of representation, and the nation's diversification.
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Regression discontinuity designs are a powerful and increasingly popular tool for causal inference. However, they suffer from a few weaknesses: handling variable data, high sensitivity to noise, and low statistical power. Even when researchers follow best practices, large treatment effect estimates can result from artifacts rather than meaningful discontinuities. These issues undermine the otherwise transparent and assumption-light causal inference that makes RDDs appealing. We introduce Bayesian change point analysis as a principled method to assess discontinuities within the regression discontinuity framework. Change point analysis efficiently identifies and evaluates discontinuities in the raw data without pre-specification. Researchers can use change point analysis to compare detected breakpoints against natural variation in the data and assess whether a discontinuity aligns with theoretical expectations. It strengthens confidence when it detects the expected discontinuity and reveals threats to interpretation, such as noise or anticipation, when it finds others. Through simulations and empirical applications, we demonstrate how change point analysis improves data visualization and validates breakpoints against theory. We provide a sequential workflow for RD analyses and introduce a software package that allows researchers to apply and visualize change point analysis in their own studies.
Slides (Updated July 17, 2024)
Poster: Asian and MENA Polmeth 24
Note: The paper is in development, but if you have comments and suggestions, please send them to bryant.moy@nyu.edu. Thanks!
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Does ideology operate in similar ways at the national and local levels? The current debate about the existence of responsiveness at the local level rest on the answer to this descriptive question. Previous studies suggest that non-ideological factors are the main drivers of local politics, while more recent research has highlighted the impact of mass/aggregate ideology on local government policies. However, the relationship between ideology and local governance is not well understood, as previous research may have conflated local-level preferences (national views disaggregated to the local level) with local-government preferences (attitudes about cities, counties, and school districts). This short article examines the relevance of self-placement ideology to local politics research. To address this issue, we conducted a survey of Americans to assess how self-placement ideology reflects individual attitudes on local taxation and spending at various levels of government (city, county, school district, and federal). We explicitly target a series of descriptive estimand of the observed ideology of individuals and their support for fiscal policy across levels of government. Our results indicate that self-placement ideology is a measure of residents' general preferences on taxation and spending, applicable across levels of government.
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Why do some ethnic groups produce local political leaders while others do not? We argue that the spatial distribution of ethnic groups within cities -- particularly their concentration into ethnic enclaves -- shapes political candidate emergence. Ethnic enclaves facilitate leadership by reducing mobilization costs, enabling targeted public goods provision, and fostering dense social and economic networks. Using a novel approach that combines machine learning classification of candidates' ethnic ancestries with spatial measures of ethnic clustering, we analyze data from 638 U.S. cities over five decades. We find that greater geographic clustering significantly increases both the emergence and electoral success of co-ethnic candidates, especially in city council elections. This relationship is nonlinear, intensifying beyond a threshold of spatial concentration. Our findings demonstrate that spatial concentration, beyond simple population share, shapes pathways to local political leadership.
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Regression discontinuity designs rest on local comparison, yet most studies do not describe the units that determine their estimates. When researchers omit that description, readers cannot know the empirical scope conditions or judge how far the findings travel. This failure to address scope conditions can stall theory development and misguide policy advice. We outline a procedure that computes kernel distance-weighted covariate means for near-cutoff units in order to describe the sample. We demonstrate our approach by re-analyzing three published studies using sharp, multi-cutoff, and fuzzy designs. In each case the analytical sample differs from the population the study purports to inform. Characterizing scope conditions facilities proper contextualization and a broader theory-informed discussion of results. An accompanying R package implements the calculations. The procedure makes sample composition explicit, clarifies empirical scope conditions, and strengthens the descriptive foundation on which causal inference rests.
* We are in the process of incorporating comments and feedback. Feel free to email me at Bryant.moy@nyu.edu with additional feedback.
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Historical housing discrimination -- specifically through racially restrictive housing covenants -- has played a central role in shaping the racial wealth gap in the United States. We test whether providing historical information about racially restrictive covenants, with or without racial visual cues, increases support for reparative measures among White Americans. In a preregistered survey experiment with approximately 5,000 White respondents, participants were randomly assigned to a pure control, a neutral housing control, or one of three restrictive covenant treatments: text only, text with a Black family image, or text with a White family image. The text-only restrictive covenant treatment increased support for reparations by 7.0 points (p < 0.001) on a 0–100 scale relative to the pure control. The text plus Black family image and the text plus White family image produced increases of 7.4 points (p < 0.001) and 5.6 points (p < 0.001), respectively. The difference between the Black family and White family image treatments was positive but not statistically significant (1.9 points, p = 0.23). Related indices (racial justice policy and white guilt) show smaller or less consistent effects. These findings indicate that factual information about racially restrictive housing covenants is sufficient to increase White support for reparations, while racial imagery may provide a minimal additional persuasive benefit. This project contributes to research on public opinion, local discrimination, and reparative policy.
Draft: May 23, 2025Presentation Slides (NYU-Madrid, May 23, 2025)
Note: The paper is in development, but if you have comments and suggestions, please send them to bryant.moy@nyu.edu and genevacole@arizona.edu. Thanks!
Research in Progress
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Police expansion poses a double-edged sword: homicides may decline, saving lives, yet petty crime enforcement disproportionately targets minority communities. We argue that Black and White Americans differ in support for additional officers because each group assigns different weight to policing's protective benefits and coercive costs. Using a preregistered survey experiment, we examine whether informational frames emphasizing homicide reductions, petty-offense arrests, or both shift public opinion on police expansion. Information about homicide reduction produces positive but small and imprecise effects among White respondents while unexpectedly decreasing support among Black respondents. The petty crime treatment significantly reduces support across all respondents, with Black Americans demonstrating substantially larger negative shifts. When both consequences are presented simultaneously, support declines for all groups, with Black Americans again showing the strongest opposition. These findings demonstrate that coercive considerations dominate protective benefits in shaping attitudes, particularly among Black Americans who perceive police expansion as an bundle of consequences. The results help explain why communities experiencing both under-protection and over-policing resist binary expand-or-defund policy choices and expose fundamental challenges for policing reform in unequal multiracial democracies.
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Anti-development coalitions often invoke market skepticism to oppose new housing construction, but market actors in housing have conflicting interests. While existing research focuses on neighborhood character and developer profits as drivers of Not In My Backyard (NIMBY) opposition, we argue that opposition depends on which economic actors citizens view as beneficiaries. Developers profit from construction, but landlords profit from scarcity. This creates a potential wedge between anti-market sentiment and housing opposition. We test this theory using a survey experiment (N=3,000) that randomly assigns respondents to six conditions: control, neighborhood character concerns, developer profit concerns, and three frames about how landlords benefit from housing scarcity through exploitation, scarcity profiteering, and wealth transfers. This research identifies landlords as distinct political actors whose interests in economic rents conflict with both developers and renters. We examine whether anti-landlord sentiment can increase support for housing development by reframing new construction as a constraint on rent-seeking rather than an enabler of it. This study contributes to understanding how economic narratives shape policy preferences, the political economy of housing markets, and potential strategies for building pro-development coalitions.
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We are currently developing a nonparametric Bayesian approach — Gaussian Process Regressions — to estimate small-area public opinion from large nationally representative surveys.
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The mayoral email archive is a novel dataset that includes non-private emails archived from the inboxes and sent boxes of mayors between January 1, 2018, and March 31, 2018. I collected these emails via a series of open records requests sent out in the summer of 2018. The open records requests were initially a part of a project on social pressure and mayoral responsiveness that was published in the Journal of Experimental Political Science in 2021.
I am currently downloading, parsing, and cleaning the email records. After the cleaning process is complete, I will incorporate the emails into my research agenda on local governance.